研究目的
To explore how a time series of high-resolution images can be used to delineate burn extent and severity, and quantify post-fire vegetation recovery, using the Waldo Canyon fire as a case study.
研究成果
High-resolution imagery and object-based approaches improve monitoring of post-fire conditions by providing detailed maps of burn severity and vegetation recovery, showing differential recovery rates among vegetation types. This can inform management decisions, but challenges remain in standardizing methods and handling image variability.
研究不足
Variability in image quality, timing, and light conditions affected interpretation; object-based approach is time-intensive and site-specific, limiting scalability; no field validation for burn severity; differences in image resolution and classification methods led to inconsistencies in burned area estimates.
1:Experimental Design and Method Selection:
Used an object-based approach with high-resolution satellite imagery (Worldview-2, Worldview-3, QuickBird-2) to map burn severity and vegetation recovery, comparing with pixel-based methods like NDVI.
2:Sample Selection and Data Sources:
Focused on the Waldo Canyon fire area in Colorado, USA, with imagery collected from 2011 to
3:List of Experimental Equipment and Materials:
20 High-resolution images from DigitalGlobe satellites, software like eCognition and PCI Geomatica, GPS units for field validation.
4:Experimental Procedures and Operational Workflow:
Images were orthorectified, atmospherically corrected, segmented into objects, classified using supervised methods and rulesets, and validated with field data.
5:Data Analysis Methods:
Used indices like BAI, SAVI, and NDVI; statistical accuracy assessments; and comparison with Landsat-based products.
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Worldview-2
Worldview-2
DigitalGlobe
High-resolution satellite imagery collection for mapping burn severity and vegetation recovery.
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Worldview-3
Worldview-3
DigitalGlobe
High-resolution satellite imagery collection for monitoring post-fire conditions.
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QuickBird-2
QuickBird-2
DigitalGlobe
High-resolution satellite imagery used in the time series for vegetation recovery analysis.
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GeoEye-1
GeoEye-1
DigitalGlobe
High-resolution satellite imagery for burned area mapping.
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eCognition
ver. 9.2.1
Trimble
Software for object-based image analysis, used to segment and classify images for burn severity and vegetation recovery.
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PCI Geomatica
Optical Satellite Modelling with the Rational Function (RPC Model)
PCI Geomatica
Software for orthorectifying satellite images.
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ATCOR
Atmospheric Correction module
PCI Geomatica
Module for converting top-of-atmosphere to ground reflectance in imagery.
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ArcGIS
10.3
ESRI
Geographic information system software for manual editing and analysis of classified outputs.
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Trimble R2 GPS
R2
Trimble
GPS unit for field data collection and validation of burn severity samples.
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Landsat
ETM+
NASA
Moderate-resolution satellite imagery used for comparison with high-resolution data.
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